Validation of prediction models based on lasso regression with multiply imputed data

BACKGROUND: In prognostic studies, the lasso technique is attractive since it improves the quality of predictions by shrinking regression coefficients, compared to predictions based on a model fitted via unpenalized maximum likelihood. Since some coefficients are set to zero, parsimony is achieved a...

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Detalles Bibliográficos
Autores principales: Musoro, Jammbe Z, Zwinderman, Aeilko H, Puhan, Milo A, ter Riet, Gerben, Geskus, Ronald B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4209042/
https://www.ncbi.nlm.nih.gov/pubmed/25323009
http://dx.doi.org/10.1186/1471-2288-14-116

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4209042/
https://www.ncbi.nlm.nih.gov/pubmed/25323009
http://dx.doi.org/10.1186/1471-2288-14-116

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